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Critical gaps remain in how chatbots are implemented across specific contexts and how their comparative effectiveness is quantified. This scoping review synthesizes existing studies to inform evidence-based future clinical practice by examining disease areas, platforms, interaction methods, architectures, implementation factors, and evaluation outcomes.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/application-of-chatbots-in-chronic-disease-management-a-scoping-review/447118/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/application-of-chatbots-in-chronic-disease-management-a-scoping-review/447118.png","ImageObject",300,407,{"name":92,"@type":93},"Indoniesian Boy","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-02","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main purpose of this scoping review?","Question",{"text":112,"@type":113},"To synthesize existing research on the application of chatbots in chronic disease management and provide evidence-based insights for future clinical practice.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were the studies identified and selected?",{"text":117,"@type":113},"Following Arksey and O’Malley’s framework, the review systematically searched eight databases from their inception until October 20, 2024, extracting data from eligible studies.",{"name":119,"@type":110,"acceptedAnswer":120},"What kinds of chronic conditions and chatbot platforms were studied?",{"text":121,"@type":113},"The included studies covered cancer, diabetes, hypertension, and other chronic diseases, using platforms such as mobile applications, web-based platforms, and instant messaging software.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},447118,1790961789,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962090760608,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Application of chatbots in chronic disease management: A scoping review  \nDIGITAL HEALTH Volume 12: 1–21 © The Author(s) 2026 Article reuse guidelines:  \n[sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)[DOI: 10.1177/20552076251411287](DOI: 10.1177/20552076251411287)[ ](DOI: 10.1177/20552076251411287)[journals.sagepub.com/home/dhj](journals.sagepub.com/home/dhj)  \nJiayi Hou 1,\\# , Shineng Lin2,\\# , Peimeng Teng 1 , Yuyuan Han 1, Yijia Luo 1  and Guijuan He 1   \nAbstract  \nBackground: Chatbots have been extensively utilized in chronic disease management to collect real-time health data, deliver personalized educational content, and guide self-management. Nevertheless, critical research gaps persist regarding their differential implementation across specific contexts and quantified comparative effectiveness.  \nObjective: To synthesize existing research on the application of chatbots in chronic disease management, providing evidence-based insights to inform future clinical practice.  \nMethods: Following Arksey and O’Malley’s framework, we systematically searched eight databases from their inception until October 20, 2024. Relevant data were extracted from eligible studies, with a focus on disease areas, application platforms, interaction methods, technical architectures, implementation elements, and evaluation indicators. The findings were then synthesized and analyzed to identify key trends and gaps in the literature.  \nResults: A total of 19 studies were included in this review, comprising 10 randomized controlled trials (RCTs) and 9 quasi-experimental studies. The investigated chronic conditions encompassed cancer, diabetes, hypertension, and other prevalent chronic diseases. Chatbot deployment platforms primarily included mobile applications, web-based platforms, and instant messaging software. The underlying technical architectures consisted of artificial intelligence-driven systems, rule-based systems, and hybrid models. The implementation strategies were categorized into night key dimensions. The predominant interaction modality was hybrid, with communication content focusing on self-management education, emotional support, and related domains. Outcome measures evaluated health-related indicators and user adherence indicators.  \nConclusions: Chatbots hold considerable clinical application value in chronic disease management. However, current research has some limitations. Future research should further optimize interaction design, refine system functionalities, and fortify privacy protection measures to better facilitate the integration of chatbots into chronic disease management.  \nKeywords  \nChatbot, chronic diseases, whole health, conversation agent, telehealth  \nReceived: 30 August 2025; accepted: 11 December 2025  \nIntroduction  \nNoncommunicable diseases (NCDs), encompassing cardiovascular diseases, malignancies, chronic respiratory diseases, diabetes, hypertension, and related conditions, represent a critical global public health challenge.1 Characterized by multifactorial etiology, prolonged disease duration, refractory nature to complete cure, and high rates of disability and mortality, NCDs exhibit persistently increasing prevalence and mortality rates. This trend imposes substantial disease burden and socioeconomic costs worldwide. 1,2 According to the World Health Organization (WHO) reports, NCDs account for  \napproximately 41 million annual deaths globally, representing 74% of total mortality worldwide.3 This challenge  \n1 School of Nursing, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China  \n2The First Clinical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China  \n\\#Jiayi Hou and Shineng Lin contributed equally to this work and should be considered co-first authors.  \nCorresponding author:  \nGuijuan He, School of Nursing, Zhejiang Chinese Medical University, No.  \n548 Binwen Road, Binjiang District, Hangzhou, Zhejiang, China.  \n","cbCaiqgwkUiRrjog","https://ap.wps.com/l/cbCaiqgwkUiRrjog","pdf",1100999,21,"English","# Abstract\n## Background\n## Objective\n## Methods\n## Results\n## Conclusions\n# Introduction\n## Noncommunicable diseases and burden\n## Digital health and WHO advocacy","[{\"question\":\"What is the main purpose of this scoping review?\",\"answer\":\"To synthesize existing research on the application of chatbots in chronic disease management and provide evidence-based insights for future clinical practice.\"},{\"question\":\"How were the studies identified and selected?\",\"answer\":\"Following Arksey and O’Malley’s framework, the review systematically searched eight databases from their inception until October 20, 2024, extracting data from eligible studies.\"},{\"question\":\"What kinds of chronic conditions and chatbot platforms were studied?\",\"answer\":\"The included studies covered cancer, diabetes, hypertension, and other chronic diseases, using platforms such as mobile applications, web-based platforms, and instant messaging software.\"}]","Application of chatbots in chronic disease management - A scoping review | PDF",1790718869,53]